Merge pull request #592 from tlm-adjoint/jrmaddison/paper_ref

Preprint -> published article
tlm-adjoint · Aug 12, 2024 · 7441732 · 7441732
2 parents 419414e + 5c5e36e
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diff --git a/docs/source/acknowledgements.rst b/docs/source/acknowledgements.rst
@@ -20,8 +20,9 @@ based on the approach described in
 
 Checkpointing with tlm_adjoint is described in
 
-- James R. Maddison, 'On the implementation of checkpointing with high-level
-  algorithmic differentiation', https://arxiv.org/abs/2305.09568v1, 2023
+- James R. Maddison, 'Step-based checkpointing with high-level algorithmic
+  differentiation', Journal of Computational Science 82, 102405, 2024,
+  doi: 10.1016/j.jocs.2024.102405
 
 References
 ----------

diff --git a/tlm_adjoint/checkpoint_schedules/mixed.py b/tlm_adjoint/checkpoint_schedules/mixed.py
@@ -148,11 +148,11 @@ class MixedCheckpointSchedule(CheckpointSchedule):
     required to restart the forward has the same size as the data required to
     advance the adjoint over a step.
 
-    An updated version of the algorithm described in
+    Described in
 
-        - James R. Maddison, 'On the implementation of checkpointing with
-          high-level algorithmic differentiation',
-          https://arxiv.org/abs/2305.09568v1, 2023
+        - James R. Maddison, 'Step-based checkpointing with high-level
+          algorithmic differentiation', Journal of Computational Science 82,
+          102405, 2024, doi: 10.1016/j.jocs.2024.102405
 
     Offline, one adjoint calculation permitted.
 

diff --git a/tlm_adjoint/checkpoint_schedules/schedule.py b/tlm_adjoint/checkpoint_schedules/schedule.py
@@ -264,9 +264,9 @@ def action_forward(cp_action):
     dependency data either for storage in checkpointing units or for immediate
     use by the adjoint. For details see
 
-        - James R. Maddison, 'On the implementation of checkpointing with
-          high-level algorithmic differentiation',
-          https://arxiv.org/abs/2305.09568v1, 2023
+        - James R. Maddison, 'Step-based checkpointing with high-level
+          algorithmic differentiation', Journal of Computational Science 82,
+          102405, 2024, doi: 10.1016/j.jocs.2024.102405
 
     In 'offline' schedules, where the number of steps in the forward
     calculation is initially known, this should be provided using the `max_n`